code: def calc_classic_noise_multi(
      total_queries, target_epsilon, delta, sensitivity
  ):
      variance = (
          8
          * total_queries
          * sensitivity**2
          * np.log(np.exp(1) + target_epsilon / delta)
      ) / target_epsilon**2
      return np.sqrt(variance)
  
file_path: interpret/python/interpret-core/interpret/utils/_privacy.py
imports: import numpy
  from scipy.stats import norm
  from scipy.optimize import brentq
  from ._native import Native
  import logging
label_desc: Use image node_id 2 for calling a global function with example usage: calc_classic_noise_multi(total_queries, target_epsilon, delta, sensitivity) and returns: np